DESCRIPTION: Purging all cells harboring proviruses that are likely to reinitiate infection could lead to a functional cure for many patients and would diminish viral spread in populations. Thus, better understanding of the latent proviral reservoir is a key public health priority. Some HIV-1 integration events lead to infectious progeny or to latent proviruses that can reactivate. In other cases, mutation during reverse transcription or epigenetic silencing makes integration a functional dead end. Latency and reactivation have been studied extensively using limited numbers of clonal cell lines or aggregate phenotypes of pooled cells. However, a better understanding of the full spectrum of reactivation phenotypes of individual unexpressed proviruses should greatly advance the long term goal of reducing blunt treatments in pursuit of a functional cure. The current application applies molecular virology, T cell development, and human genomics approaches to a novel high-throughput method for better defining classes of latently infected cells and their signatures of reactivation. Studies proposed for the R21 exploratory phase will develop a novel barcoded provirus technology and validate its use in cultured cells, establish technologies to enable this system in primary T-cells, and develop the bioinformatics for high throughput analysis of large numbers of individual integrants in a test case that addresses the extent to which silencing in a T cell line is determined by integration location vs. stochastic effects. In R33 phase proof-of- concept studies, the barcoded provirus system will be further refined and applied to defining molecular and genomic signatures of reactivation and persistence in response to cellular differentiation or therapeutic reactivation inT cell lines and primary CD4+ T-cells, to studying the relationship between latency and functional diversity of CD4 effector T cells, and to evaluating the potential of a novel molecular genetic approach for tracking the clonality of residual viremia, which may in the future be applied to patient samples.